How to Win Big in the First 100 Days as a New CDO

Keeping a business consistently data-driven isn’t easy. Vast quantities of potentially valuable company and consumer data lie locked away in corporate silos or lost in cross-functional translation. To unlock the hidden value in all this data, organisations are increasingly turning to the newest member of the C-suite, the CDO. 

TABLE OF CONTENT

Chapter 1: What is a CDO and Why are they Important?
What does a CDO do?
The key to becoming a successful CDO

Chapter 2: First 30 days – Meet and Greet Stakeholders to Identify Business Goals
Explaining the role, making a case for change
Identifying long-term corporate strategy & concrete business objectives
Securing executive sponsorship

Chapter 3: Next Steps – Assess the Company’s Existing Data
Evaluating Data Quality with a quick assessment
Identifying dirty data and information weaknesses

Chapter 4: What Now? Assess the Organisation’s Data Maturity & Capability
Mapping data hand-offs & business processes
Aligning IT with business objectives
Building Business Glossaries and defining CDEs
Encouraging a data-driven corporate culture

Chapter 5: Draft a Roadmap, Set KPIs and Get Sign-Off

Linking specific data elements to critical business objectives 
Establishing a roadmap and setting KPIs
Securing Sign-Off from key stakeholders

Chapter 6: Getting Started! 
Implementing Data Governance structures
Building stronger Business Glossaries, expanding CDEs & monitoring DQ
Continuously demonstrating value
If it involves data and impacts the bottom line, the CDO has got it covered.

Chapter 1: What is a CDO and Why are they Important?

Like any freshly minted job title, there’s still a bit of ambiguity surrounding the role and responsibilities of a CDO.

A CDO is a Chief Data Officer. Their job is to make sure that company data is being put to work. They’re an organisation’s digital change leader, responsible for ensuring that critical business decisions are being backed up by bulletproof data.

Simple enough, but this is where things start to get confusing.

As a relatively newfangled title, CDOs aren’t always labelled “CDOs.”  If they’re in the C-suite they might be called Chief Digital or Data & Analytics  Officers. If they report into a CIO, CFO or a COO you might be used to calling them Data Product Managers, Data Management Specialists, or more rarely, Data Governance Analysts.

What does a CDO do?

Whatever they’re called, organisations depend on a CDO to:

  • Spearhead Data Governance initiatives 
  • Draft, implement and maintain corporate Data Strategies
  • Develop business and data glossaries to improve cross-functional communication
  • Streamline operations and improve customer relationships with data
  • Optimise data collection, management, and handling practices
  • Ensure data privacy, security, and compliance
  • Evangelise for data-driven decision making

If that seems like a terrifically broad set of responsibilities, that’s because it is. A CDO functions as a single point of contact for virtually all of an organisation’s strategic data. If it concerns data and can be leveraged to improve the bottom line, the CDO has got it covered.

In today’s data deluged corporate environment, organisations are just as likely to suffer from an overabundance of data as they are from a lack of it. 

Unfortunately, that means that when data-related issues arise—and they always do—companies struggle to determine whom to turn to for solutions. Operations? IT? The CDO serves as the ultimate backstop, maintaining a holistic, macro-level view of an organisation’s data—what it’s doing, where it’s stored, and who’s responsible for it. They’re the ultimate solution to information bottlenecks and departmental data silos.

To facilitate cross-functional cooperation and ensure that company data is being catalogued and communicated effectively, CDOs are invested with a mandate to establish principles, policies, and guidelines. In other words, it’s their job to ensure that the rest of the organisation remains accountable to a single, consistent Data Strategy.

There’s a common misconception that Chief Data Officers need to come from a tech-heavy background. Nothing could be further from the truth. CDOs should be thought of as strategic business managers rather than IT whizzes. They don’t need to be experts in AI or algorithms, and they don’t need to arrive with ready-made solutions on day one of the job.

READ MORE: Cognopia’s List of Frequently Asked Data Governance Questions

The key to becoming a successful CDO

In fact, to draft a Data Strategy that’s well-aligned with the business, a CDO needs to spend a considerable amount of time just getting acquainted with a new organisation—that means learning about its business goals as well as developing rapport with key stakeholders. 

At the end of the day, a CDOs effectiveness will always depend on their ability to influence decision-makers and rally support for change—not an easy thing to do.

According to Gartner, by 2019, 90% of large organisations had already hired a CDO, but only 50% of these CDOs will ultimately prove successful. The difference between success and failure hinges largely on how a CDO approaches their first 100 days on the job. 

So let’s see how to get things right from day one.

Chapter 2: First 30 days – Meet and Greet Stakeholders to Identify Business Goals

A CDO should spend 50% of their first 100 days meeting and greeting senior stakeholders.

To set themselves up for success a CDO should spend as much as 50% of their first 100 days meeting and greeting senior leaders from various departments—business, operations, sales and IT especially. 

The goal here is to build rapport with key stakeholders and develop a better understanding of the organisation’s critical business objectives, as well as to gain an understanding of how ready the business is for Data Governance.

READ MORE: How to know if your Company is Ready for Data Governance

50% of the first 100 days may seem like a huge amount of time to invest in meetings, but the benefits of building strong relationships and a clear, early understanding of the organisation’s pain-points really can’t be overestimated. 

Explaining the role, making a case for change

The CDO will need to explain their role to business line leaders and senior staff—all of whom need to have a clear idea of how the CDO will be able to help them accomplish their case-specific business goals.

READ MORE: Getting Management Buy-In For Data Governance

A lot of organisations make the mistake of conceptualising data purely in terms of liability or costs, rather than benefits. It’s the CDO’s job to explain to the rest of the C-suite that data is a major business-driver, something that can and should be leveraged to improve the bottom line. In other words, it’s up to the CDO to explain what Data Governance is all about.

Data Governance is a strategic business program for optimising the way an organisation deals with data. It involves people, processes and IT, and aims to reorganise and improve the way a company defines, collects, stores, secures, manages, and monetises its data.

At the very least, a Data Governance program will involve:

  • Evaluating and redefining roles and responsibilities
  • Augmenting policies to improve communication and sharing between departments
  • Defining and expanding access to business-critical data
  • Standardising data collection and management practices to improve the quality and consistency of data

Data Governance not only helps companies avoid liability, but to save time and money on bad data, improve customer relationships, and actively generate new value streams as well. 

Getting management to understand the benefits of good Data Governance can be tough, but until an organisation’s CFO and CDO start seeing eye to eye, the business and its customers will continue losing out. To secure buy-in, the CDO needs to be able to make a persuasive and relatable case for change.

That might be as simple as showing how good data can help sales teams improve customer relationships and increase the performance of marketing campaigns, or how operations and finance teams can enhance performance management and increase efficiency.

To really win over corporate, the CDO will need facts and figures, so consider the following. According to McKinsey, data-driven organisations are 23 times more likely to acquire customers, six times as likely to retain customers and 19 times as likely to be profitable as a result. 

What’s more, good Data Governance can see an average of 69% less time spent locating data and reports, 28% lower frequency of data-related errors, and 23% higher gross productivity. 

All that time saved sifting through dirty data can translate into some impressive ROI, as much as 500% in some cases.  This ‘corporate benefits’ mindset should always be at the forefront of the CDO’s pitch to management.

Identifying long-term corporate strategy & concrete business objectives

To craft an effective Data Strategy in the days ahead, the CDO will need a crystal clear understanding of the organisation’s critical business objectives. To that end, the CDO should be using these early stakeholder meetings to learn as much as they can about the organisation’s long term corporate strategy and concrete business goals. 

Each executive meeting should be viewed as an opportunity to gather insight into the wants and needs of a new department. As the CDO learns more about each stakeholder’s unique business case, they should already be asking themselves how data can be used to relieve pain points, reduce friction, and improve the company’s products, services, and internal workflows.

To keep their meetings productive, the CDO should also prepare a handful of thoughtful questions in advance. This is a golden opportunity to suss out chronic pain-points and generate insights about previous Data Governance or Data Management related mishaps as well, so a CDO will absolutely want to get this right. Too few questions and they risk glossing over important details, too many and they risk getting caught up in minutiae.

Given the sheer number of meetings, a CDO will face in their first 100 days, a bit of prep work is advisable. The CDO will want to learn as much as they can about the company before showing up for work on day one—everything from financial reports to noteworthy recent hires can prove helpful. It’s not uncommon for CDOs to even set up meetings with business and IT execs before their official start date—anything to help get a better big picture view of the organisation.     

For the CDO, these meetings are as much about making a favourable first impression as they are about information gathering, so it’s an equally good idea to prepare some introductory personal material. Anything that can help establish the CDO’s credentials or simply ease those clunky first-day communications will help ensure a confident head start.  

Securing executive sponsorship

A CDO’s first priority should be securing a meeting with the CEO. There’s no better way to form a top-level impression of the organisation’s existing Data Strategy—or its lack thereof. The CDO should aim to come away from this meeting with a firm grasp of the perceived role and use of data across the company. 

  • Is data regarded primarily as a liability, something to be kept safeguarded and secure, or is it being mobilised as an active and universal business asset?
  • Is the management of company data being relegated to IT, or does the business play an active role in daily Data Management?
  • Has the organization tried and failed to implement Data Governance in the past? If so, what went wrong?
  • Are decisions being made based on hard data, or are gut instincts driving the show?

Answering these questions will tell the CDO an extraordinary amount about the company’s existing data culture while highlighting likely stumbling blocks on the road ahead.

In addition to clarifying the CEO’s goals and expectations, the CDO should also use this meeting as a chance to secure executive sponsorship for future data initiatives. If they can ensure the CEO’s support, meeting and mapping out the priorities and goals of the remaining executives should be a relative breeze.

Finding a committed executive sponsor can be challenging, but it’s not impossible. The CDO needs to excite their sponsor-to-be with the benefits of good Data Governance. If their pitch is aligned with corporate strategy and they remember to keep the organisation’s business objectives front and center, they shouldn’t have a problem.

The CDO shouldn’t be concerned with making big structural changes right off the bat. The point of all this networking and information gathering is to form an accurate picture of what the business needs, and to begin exploring how data can be used to achieve those goals. When the time is right, this will allow the CDO to state with confidence exactly what needs to be done.

To avoid wasting time and money building capability for capability’s sake alone, the CDO must remain constantly grounded in this business-first mindset. Plus, keeping business needs front and centre should clarify what the CDO will and won’t be doing in the days ahead. 

Chapter 3: Next Steps – Assess the Company’s Existing Data

A CDO needs to work with IT to assess the quality of existing data.

With a firm grasp of the organisation’s long-term corporate strategy and concrete business goals, and a clear view of the organisation’s key executive stakeholders, the CDO is ready to move on to the next phase of their first 100 days.

The CDO’s next step is to work with the CIO and IT teams to understand the company’s current data landscape. 

This includes taking stock of the business’ current data platforms, architectures, and analytics solutions, as well as getting briefed on existing data collection, quality, handling, storage, and communication practices. 

The CDO should also assess the technical capability of data handling personnel (e.g. the Data and Analytics team). An organisation may have all the data it needs but still lack the technical skills required to effectively put it to use. 

Remember: the CDO shouldn’t be looking to make any major changes right out of the gate—this phase is still all about orientation and assessment.

Evaluating Data Quality

To get the full measure of the organisation’s existing data, the CDO will want to get started conducting various data audits, keeping a close eye out for any major Data Quality issues. 

Data Quality refers to whether or not a particular data element or set is fit for purpose. If a particular data point can achieve the goals that have been set for it, then it’s considered high quality. Without high-quality data, an organisation risks making business-critical decisions on completely faulty assumptions.

It’s often tempting to think of Data Quality wholly in terms of accuracy, completeness, reliability, or timeliness—and those are all key, easily measurable parts of it—but Data Quality is about relevance as well. Even a flawless, error-free data set can still fail to perform the task or function it’s been assigned. In that case, it’s still not fit for purpose—it’s still not high-quality data. The CDO will need to keep this strategic aspect of Data Quality in mind throughout this phase.    

It’s also essential that the CDO understands precisely what “fit-for-purpose” means in the context of any given business case—if criteria for usefulness haven’t yet been clearly defined, the CDO will need to establish them before moving forward.

Clearly, assessing the organisation’s data landscape is about much more than just building an inventory of catalogs and assets—the CDO needs to have an idea of not only what data is available, but of what that data can do for the business:

  • Is it fit-for-purpose or is it providing insights that are irrelevant to customer experiences? 
  • Can existing data be successfully leveraged to accomplish the organisation’s business goals or are there notable gaps in data collection and quality processes?

READ MORE: 5 Best Tools for Determining Data Quality  

Depending on the size of the organisation and the complexity of its IT landscape, running a thorough data audit—to say nothing of strategically assessing the business value of the data itself—can take an exceptionally long time, so it’s best to join forces with IT and delegate tasks accordingly. 

At this stage, the CDO shouldn’t worry about auditing all of the organisation’s existing data—a practically impossible chore. Instead, they should take what author and President of Data Quality Solutions, Tom Redman, calls a  “Friday Afternoon Measurement” approach to get a quick and dirty view of any major problems. 

To pull this off the CDO should settle on a single operation or area of focus, say customer support for example. With this single operation or process in mind, the CDO should then cherry-pick 10-15 data attributes that need to be perfect in order to carry out that operation to completion—e.g. customer name, account number, etc. 

The CDO should then map out the last 100 records that have been handled—in this case, customer records— and evaluate the status of those essential data attributes. If they’re incorrect, missing or invalid then they’re marked as false. Any data record with even a single false attribute is incorrect as a whole. The total number of incorrect records represents a rough percentage gauge of the organisation’s overall Data Quality score.

The CDO will need to do everything they can to convince management that there’s no such thing as “good enough” where Data Quality is concerned. Tom Redman has an excellent example demonstrating why this is the case:

 Say that your company has 100 data records, and each data record costs $1 to produce. Now let's say that your data is 99% accurate. Good enough, right? Well, not exactly. That 1 inaccurate data record isn’t just a dollar wasted. Using the ‘rule of ten’ it's more likely to cost you closer to $10 in downstream errors, lost opportunities, and cleanup time.

Now consider that in the real world, each one of your data records will contain multiple data elements, each of which has the potential to be off.  Say that each of your data records contains 12 fields. Even with 99% accuracy, you’ll still see, on average, 12 inaccurate fields per 100 data records. And these 12 field errors aren’t going to be conveniently found side by side in just one data record either. It's much more likely that they’re going to result in 12 inaccurate data records.

Rather than the 99 accurate data records that we started with, you’re now looking at just 88 correct ones. That means that even at 99% accuracy, you’ll end up spending $88 dollars for the 88 accurate data records, but a whopping $120 in cleanup for just the 12 inaccurate ones. That’s a total of $208, wasting $108 on "non-value-added" work for every $100 of actual work product; in other words, a 52% wasted effort.

If the CDO walks management through the numbers they’ll have made a great case for why improving company data can, should and must be taken seriously.

Identifying dirty data and information weaknesses

After roughly evaluating the quality of the organisation’s data, the CDO’s next goal should be to identify any further weaknesses in the company’s existing Data Management practices. As with Data Quality issues, the CDO should categorise these weaknesses according to their severity and prioritise future solutions accordingly. 

With a fresh set of strategically aligned eyes, the CDO is likely to uncover a number of dirty data issues, among them: 

  • Missing data definitions; unclear or undefined Critical Data Elements; 
  • Missing data; fields that are incomplete or inaccurate;
  • Data timeliness issues; updates not propagating to the teams or systems that need fresh data;
  • Organisational silos and incompatible KPIs;
  • Poorly integrated systems landscape, with no unifying business strategy;
  • Dated data platforms or architectures; 
  • Unnecessary or unhelpful tools; 
  • Legacy issues from previous data initiatives that haven’t yet been cleaned up.

Some issues will require complex, institutional or structural corrections, while others may be as simple to fix as clicking a button or shopping around for a more effective tool. 

While investing in a powerful Data Quality tool or Data Management software can seem like a fix-all solution to a company’s dirty data, the truth is that tools are just a small part of a larger picture. The CDO should always focus on developing the company’s personnel and internal processes before investing in tools. After all, what use is high-quality data if the organisation has no clear way to define, share, or act upon it in the first place?

After documenting the state of the company’s existing data and flagging any obvious problems, the CDO’s next step is to ask themselves if the organisation actually has enough data to reasonably accomplish its goals.

  • If the answer is no, then the CDO needs to kick-start new data collection and sharing practices to equip the company with all of the essential information it needs. 
  • If the answer is yes—the organisation has sufficient data that’s fit-for-purpose—then the CDO is ready to begin strategising how to put that data to work. 

This leads us to the next and final preparatory phase of the CDO’s first 100 days.

Chapter 4: What Now? Assess the Organisation’s Data Maturity & Capability

data-governance-roles
A CDO needs to have a clear view of everyone’s roles and responsibilities.

Now that the CDO has a better understanding of the company’s existing data, it’s time to determine whether the organisation is capable of putting it to good use.

This phase is all about developing an understanding of organisational capability—in other words, it’s about assessing Data Maturity

Data Maturity is all about evaluating the people, processes and systems that utilise company data.

READ MORE: Data Maturity Issues and How to Solve Them

Mapping data hand-offs with business processes and clarifying roles and responsibilities

The CDO needs to map out how data flows and is handed off through the organisation—where it originates, who manages it, how it’s organised and communicated, and ultimately how it’s applied to real-world business operations. This can be more challenging than it sounds since many organisations struggle with ambiguity over who owns and is accountable for data.

Further complicating the issue, staff from different departments and different levels of seniority are likely to have conflicting ideas about precisely who is responsible for what. That means that the CDO can’t dependably rely on the impressions or experiences of any single coworker. Instead, they’ll need to develop their own understanding of how data is being transmitted within and between departments, keeping an eye out for bottlenecks, silos, and black holes that may be costing the organisation considerable sums.

A disproportionate number of Data Maturity issues stem from misunderstandings about the roles and responsibilities of individual personnel.

data governance business roles

To address these issues, the CDO needs to determine whether or not Data Owners, Data Stewards, and all other data handling employees actually know what’s expected of them. 

  • Are there clear and consistent policies in place to inform how data is collected, handled, stored, archived, updated, shared and applied? 
  • Just as importantly, are there mechanisms in place to change those policies should the need arise?

The CDO should also determine if there are clearly designated distinctions between Data Owners (senior staff accountable for the fitness of a particular data set) and Data Stewards (staff responsible for the daily management of those data sets). In some smaller organisations just one person might perform both these roles, but to ensure transparency and accountability, as well as to encourage engagement from multiple departments, it’s usually best to divide them up.

At this phase in their first 100 days, the CDO should also be keeping an eye out for misplaced or neglected talent.

READ MORE: How to know if your Company is Ready for Data Governance

Aligning IT with business objectives

A surprising number of IT teams and subject matter experts wind up wasting time on projects that won’t actually benefit the bottom line. It’s essential to gauge whether or not IT teams are strategically aligned with the organisation’s business objectives, and if not, to begin thinking about how their time and effort could be put to more productive use.

Of course, even with a perfectly business-aligned IT department and all the high-quality data in the world, a dysfunctional decision-making process can still derail an organisation’s Data Maturity. 

When relevant teams or departments are excluded from critical decision making, top-level strategies and goals can be miscommunicated, and essential data elements can get overlooked, misinterpreted or misapplied. Simple communication and engagement issues like this can deal an outsized blow to the bottom line, so it’s crucial that the CDO identifies whether any key stakeholders are being neglected early on.  

One quick and highly effective way to ensure that every relevant department is being included in the decision-making process is to appoint Data Owners from each and every team involved in the organisation’s prioritized business objectives. This will guarantee that critical data is being carefully considered and digested across the organisation, increasing the odds that it will be applied effectively when needed.

Of course, simply appointing Data Owners from a variety of departments is no guarantee that data will be communicated or understood effectively. 

Building Business Glossaries and defining CDEs

Without a Business Glossary to establish common terminology, any discussion can quickly turn into a data brawl. Individual departments will have their own, often incompatible interpretations of the same numbers. 

For example, a sales team might think that a customer is anyone who has ever bought anything, whereas a finance team might restrict that definition to those who are actively paying invoices. Presented with the very same data, the two teams will come to radically different conclusions, and neither will be able to make a confident, data-driven decision for the business. To prevent this from happening, Business Glossaries are essential. 

Business Glossaries define the meaning, format and uses of an organisation’s commonly used business terms and Critical Data Elements (CDEs), and are essential for keeping everyone on the same page. By contextualising and defining individual data elements, they improve business understanding, save time on searching for reports and prevent accidental misuse.

A huge part of constructing Business Glossaries revolves around identifying and properly defining an organisation’s Critical Data Elements (CDEs). 

The CDO will need to determine if the organisation has defined its CDEs at all—and if so, to further determine whether they actually represent the data elements that most heavily impact the company’s bottom line. 

Defining CDEs should be a collaborative and cross-functional project, since each department is likely to have its own case-specific needs and goals.

There are a number of ways to approach prioritising CDEs. Whichever approach a CDO takes, they should be sure to keep the organisation’s business objectives close in mind. 

One general approach for defining CDEs involves identifying an organisation’s critical business processes. The CDO can reliably prioritise any of the data used to ensure that these processes run, as well as any data used to report on their progress (either internally or externally). The CDO should also include any data that might cause a process to fail or damage the company if it were hacked or stolen.

Another great way to identify and prioritise CDEs is by mapping out the organisation’s customer journeys. The CDO should keep an eye out for each and every data touchpoint where friction can be reduced or services and customer relationships can be improved. The data elements involved in these touchpoints are great candidates for CDEs. 

critical data element flowchart

The ultimate goal behind defining CDEs and building Business Glossaries is to provide the company’s key decision-makers with a consistent understanding of all the data that’s most likely to generate value for the business. 

With a common understanding achieved and essential data in hand, the organisation will be far more capable of making confident, data-driven business decisions. In other words, it will be far more data mature.

This brings us to the last, though certainly not the least important consideration for this phase. 

Encouraging a data-driven corporate culture

Even if the CDO is able to provide executive decision-makers with bulletproof data and cohesive Business Glossaries, the business still may not behave in a genuinely data-driven way.

To seal the deal on Data Maturity, the CDO will need to ensure that the organisation is treating data as a universal business asset, rather than just “some IT thing” to be ignored or pushed aside.

If data isn’t being treated as an enterprise asset, the CDO will need to begin winning over senior level sponsors to help them really make the case for change.

Another way to win over hearts and minds is to find a motivated business unit and run some kind of proof of concept. If the CDO can demonstrate the quantifiable benefits of data-driven operations, they’re far more likely to persuade the rest of the organisation to get on board.  

At this point in their first 100 days, the CDO should have:

  • Identified the organisation’s business goals and determined how data can be used to achieve them.
  • Surveyed the state of the company’s critical information, where it resides, how it can be accessed, and by whom.
  • Mapped out how data moves through the organisation and identified problems such as dead-ends, bottlenecks, and black holes.
  • Know what if any structural changes need to be made in order to clarify roles and responsibilities, improve communications, and encourage a more data-driven corporate culture.

With all this prep-work and assessment completed, the CDO is at last ready to get to work.

Chapter 5: Draft a Roadmap, Set KPIs and Get Sign-Off

A good roadmap should be uniquely tailored to the business’ needs.

This is the post-assessment phase when it’s finally time for the CDO to put everything they’ve learned to use. Having identified the organisation’s major technical, structural and procedural pain-points, it’s time for the CDO to begin implementing solutions. 

The first step is to draft a battle-plan—a bespoke roadmap of data initiatives uniquely tailored to the organisation’s business needs.

Linking specific data elements to critical business objectives

If the CDO has spent their time wisely and developed a solid understanding of both the business and its technical assets, they shouldn’t have much trouble identifying business operations that can already be improved with existing company data. This is all about identifying how to put underutilised or misunderstood data to work.

The next step involves providing the organisation with any additional information it needs to accomplish its goals. In other words, if the organisation is missing data that could improve critical business operations or decision making, the CDO should work with the company’s Data Owners, Data Stewards and Data Producers to begin filling in the gaps. 

This is largely about altering Data Management and collection practices to provide actionable information where none currently exists. It may also involve a number of related Data Governance initiatives, such as using Business Glossaries to break down silos and strengthen underdeveloped data through better communication.

Establishing a roadmap and setting KPIs

Now that the CDO has matched specific value-generating data elements to corresponding business use-cases, it’s time for a roadmap. This is where things begin to take on a much more concrete form.

Before sharing their roadmap with key stakeholders and managing executives, the CDO needs to establish a realistic timeline with firm KPIs (key performance indicators). 

KPIs are absolutely essential for meaningfully measuring progress, as well as for keeping the CDO and all of their activities fully accountable to the business. They’re also one of the most pragmatic ways for the CDO to set clear expectations and define precisely what success will look like.

To ensure that all of their data initiatives remain consistently business-focused, the CDO should tie all of their KPIs to quantifiable business milestones rather than technical accomplishments alone. 

KPIs could reflect cost savings or optimisations, improvements in sales, marketing conversions and churn rates, or even numbers of additional services developed with better data. KPIs should also reflect the activities of the organisation’s Data Owners. 

Common KPIs for Data Owners include:
 
Increasing the number of data elements in the Business Glossary
in terms of the total number of data elements accepted
in terms of the total number of data elements added in the past day/week/month

Increasing the number of business terms in the Business Glossary
in terms of the total number of business terms proposed
in terms of the total number of business terms approved

Increasing the number of Data Quality rules observed by Data Stewards
in terms of the total number of Data Quality rules accepted
in terms of the total number of Data Quality rules in operation

Improving the number of new data issues identified and resolved by Data Stewards
in terms of the total number of unresolved data issues
in terms of number of data issues resolved in the past day/week/month

Whichever KPIs the CDO settles on, they should ideally be expressed in terms of dollars and cents and have clear ramifications for the bottom line. 

Tip: CDO’s should keep both their KPIs and their timeline as realistic as possible—after all, big changes take time.

Securing sign-off from key stakeholders

With their Data Strategy drafted, their program timeline established and quantifiable targets set, the CDO is at last ready to share their work with the organisation’s key stakeholders. This is where all that relationship building and executive sponsorship really begins to pay off. 

To gain approval and secure a budget, the CDO will once again need to articulate the business value of their Data Strategy. The CDO can support their ideas with an assessment of where the organisation currently stands against a model of where it wants to be. The goal is to demonstrate how the CDO’s plan will close that gap through concrete, actionable projects.

If the CDO has already secured support from senior staff across the organisation, then garnering approval for their plans shouldn’t be too difficult. Even so, the CDO will need to ensure long-term organisation-wide commitment if they want their strategy to succeed in practice.

To guarantee that level of engagement, the CDO needs to do more than just earn management’s begrudging approval—they need to win hearts and minds, to “wow” the rest of the C-suite. 

To that end, it’s a good idea to keep the conversation simple. The CDO needs to explain exactly what they intend to do, how long it will take, and how it will generate value for each and every stakeholder’s unique business case.

If the CDO faces serious push-back, they should once again consider running a series of trial projects to demonstrate ROI and win over reticent business units. Obviously, this can be a major time-suck, so it’s best to put in the extra diplomatic effort early on and avoid the problem altogether.     

If the CDO manages to secure sign-off and obtain a budget, then all that remains is action.

Chapter 6: Getting Started!

A data governance council involves senior staff from across the organisation.

With a clear roadmap drafted and their plans signed off, the CDO is finally ready to get to work. To lay a strong foundation for all of their future data initiatives, as well as to ensure at least a few early successes, the CDO should start things off by implementing or refining the organisation’s Data Governance structures.  

Implementing Data Governance structures

data governance structure

The foundation of any good data initiative is a robust governance structure. The CDO’s executive sponsor will typically oversee a steering committee responsible for enforcing standards, distributing accountability, measuring progress and clearing roadblocks. 

data governance steering committee

Below this steering committee, the CDO will need to assemble a Data Governance Council. The aim of this council is to direct and coordinate all of the organisation’s data-handling teams, to ensure sustained commitment to Data Management policies and practices, and to arbitrate on any issues that Data Stewards aren’t able to resolve on their own. In other words, they’re the driving force behind the CDO’s entire plan of attack.

If the organisation doesn’t yet have a Data Governance Council in place, the CDO should now immediately begin bringing one together.

Data Governance Councils are comprised of executive or senior staff from both business and IT, as well as subject matter experts from various departments. It’s a good idea to ensure that most if not all of the organisation’s Data Owners are also included in this council. This will help ensure that top-level strategies are being informed by up to date intel, as well as that they’re being effectively communicated to the working teams responsible for carrying them out.

The CDO’s main role in the Data Governance Council is to ensure that everyone else understands and performs their duties according to plan. That means continuously helping to clarify the roles and responsibilities of all data handling personnel, as well as monitoring precisely who the organisation’s Data Owners and Data Stewards are. 

To identify appropriate candidates for Data Owners,  the CDO just needs to follow the money. Who loses the most if a particular data element or set isn’t up to par? The person with the most on the line is typically the best choice for that data element or set’s owner. 

With clear Data Governance structures in place, policies and guidelines will be far easier to implement, amend and alter down the line. This is essential, since the CDO should be thinking of their current roadmap as more of a draft than a finished product. To continuously deliver value to the business, the CDO will need to make a number of minor changes and course corrections in the days and weeks ahead.

Building stronger Business Glossaries, expanding CDEs & monitoring DQ

With solid Data Governance structures in place, the CDO should now meet with each working team to once again discuss their KPIs and strategise how best to meet them. The CDO may have already developed rapport with management, but now’s the time to build trusted partnerships with the rest of the operational staff.

It’s time for the CDO to roll up their sleeves and get to work alongside their new colleagues. They should continuously strive to build better, stronger Business Glossaries, to expand and deepen their understanding of the organisation’s Critical Data Elements (CDEs), and to work closely with Data Stewards—and owners—to monitor and improve Data Quality.

This will be a continuous and cyclical process for the CDO. They’ll work with operational teams to implement the company’s top-level Data Strategy, delivering continuously improving data against concrete business objectives. They’ll also regularly meet with senior stakeholders and executive staff to refine that top-level strategy, ensuring that it remains consistently tied to corporate goals.

Continuously demonstrating value

This process is all about continuously demonstrating value to the business. To maintain the support of their peers in management, the CDO should strive to rack up as many quick successes as they can. Even as time goes on and more and more individual projects get completed, the CDO will still need to communicate precisely how they’re generating value for each and every stakeholder.

With their first 100 days drawing to a close, the CDO will need to need to continuously test and iterate on their initial roadmap—touching base with team managers and executive stakeholders for regular progress reports.

If a strong foundation is already in place, a handful of early victories are all but guaranteed—just the thing for ensuring that the CDO enters their next 100 days set for success.  

Cognopia is Here to Help

A CDO’s first 100 days can be tough, but Cognopia is here to help.

From identifying corporate strategy and winning executive buy-in to auditing company databases, prioritising CDEs and drafting Business Glossaries, a Chief Data Officer’s first 100 days are anything but easy. 

CDOs are expected to wear a multitude of hats, serving as simultaneous business strategists, Data Management gurus, and corporate diplomats—but they don’t have to go it alone. Cognopia is here to help.

READ MORE: What to look for in a Data Governance Consultant

Want to learn more about Data Quality, Data Maturity, or the bigger picture of Data Governance? Struggling to find Data Management software that’s right for your business? Not sure if your company is even ready for Data Governance in the first place? 

With free Data Maturity assessments and a range of bespoke consulting services, Cognopia’s team of Data Governance experts will help you craft a bulletproof Data Strategy unique to your organisation’s needs.

We turn data into rocket fuel for your business, powering your organisation with information that works. 
Schedule a chat here and find out what Cognopia can do for you.